Eventually you get to a point in the process where you make an edit and you are not even sure if it was a positive change or not.

If you want to get an idea of how hard it can be just to select colors, watch this YouTube talk about the process matplotlib went through to redesign their default colormap.

Fortunately, Tableau does the heavy lifting of design choices for you, and 9 times out of 10, it looks great.

I asked a colleague why he likes Tableau, and he said, “It makes your data look pretty, and you don’t even have to try”.

The value of pretty shouldn’t be underestimated.

In a chart, beauty is often the absence of distractions.

If the colors are off, or there are too many tick marks, this distracts the audience from the message of the data.

Florence Nightingale has a great example of this.

She used a polar area diagram that is simple with minimal distraction, allowing the audience to instead focus on the story the data is telling (here’s a link to a Tableau workbook some make replicating Nightingale’s famous graph).

Sadly, other visualization tools are still behind in this area.

This out-of-the-box beauty from Tableau, combined with its balanced approach to user ease, has made it the de facto tool for data exploration and visualization.

Tableau users are in every industry and across any job function.

In fact, maybe the only data tool that is more ubiquitous than Tableau is Excel.

An Ode to TableauI have always really enjoyed Tableau.

It’s a wonderful product that provides a great service.

When I heard the news that they were acquired, my first thought was that I was happy for them.